Light pollution significantly interferes with animal and human life and should, therefore, be included in the factors that threaten ecosystems. The main aim of this research is to develop a methodology for monitoring environmental and social elements subjected to light pollution in anthropogenic areas. This research is based on yearly and monthly photographs acquired from the Visible Infrared Imaging Radiometer Suite (VIIRS) onboard the Suomi National Polar-Orbiting Partnership (Suomi NPP) satellite; land cover data from the CORINE Land Cover (CLC) program; and environmental data from the European Environment Agency (EEA) and the World Database on Protected Areas (WDPA). The processing of input data for further analyses, the testing of the methodology and the interpretation of the final results were performed in GIS-type software (ArcGIS Pro). Light pollution in the investigated area was analyzed with the use of maps generated for the years 2014 and 2019. The environmental and social elements were spatially identified in five light pollution classes. The research results demonstrate that the proposed methodology allows for the identification of environmental and social elements that emit light, as well as those that are subjected to light pollution. The methodology used in this work allows us to observe changes resulting from light pollution (decreasing or increasing the intensity). Owing to the use of publicly available data, the methodology can be applied to light pollution monitoring as part of spatial planning in anthropogenic areas. The proposed methodology makes it possible to cover the area exposed to light pollution and to observe (almost online) the environmental and social changes resulting from reductions in light emitted by anthropogenic areas.

Mobile Mapping Technology (MMT) has evolved rapidly over the past few decades, especially in using low-cost sensors. This progress is primarily attributed to the appearance of innovative simultaneous localization and mapping (SLAM) algorithms. This article focuses on evaluating the efficiency of a new LiDAR-based portable SLAM system for mapping in dynamic real-world environments. The work proposed a technical solution based on a Livox Avia LiDAR sensor enhanced by gimbal stabilization. The system, named Portable Livox-based Mapping system (PoLiMap), is compared to other similar solutions by acquiring data from various environments, including urban sceneries, underground tunnels and forested areas, and processing them using a modified FAST-LIO-SLAM algorithm. The research presented in the article contributes to the understanding of the capabilities of PoLiMap systems under various conditions and offers significant insight into its potential applications. Accuracy evaluation results prove that the proposed MMT system can successfully tackle various demanding environments and challenge the results of other more costly state-of-the-art portable mobile laser scanning methods.

Sensors are a key component of virtual reality (VR) technology, as they enable motion tracking, interaction with the environment, and realistic representation of user behaviour in virtual space. VR technology is gaining increasing importance in engineering, offering new ways to support research, analysis, and training. This article examines its applications in four key areas: surveying and geomatics, mining, environmental protection, and occupational safety. The study is based on a review of the scientific literature indexed in the Scopus database, with the aim of highlighting both the potential of VR and directions for its future development. The findings indicate that VR provides effective tools for analyzing, interpreting, and visualizing complex geospatial data. It enables realistic simulations of mining processes, supports the monitoring of environmental impacts, and facilitates environmental education by creating engaging, immersive experiences. In occupational safety, VR allows hazard scenarios and accident events to be reproduced in a safe yet highly realistic environment, significantly enhancing the effectiveness of training. This is made possible through the integration of sensors with virtual reality, further enhancing immersion in the environment. Despite these advantages, several barriers have been identified. They include technological challenges, insufficient numbers of trained specialists, health and ergonomics concerns, resistance to organizational change, ethical considerations, and limited funding. It is clear that the future of VR in engineering will be shaped by continuous technological progress combined with growing attention to behavioural aspects of training and user interaction. These trends are expected to drive the creation of increasingly advanced and effective tools. The article thus provides a foundation for further exploration of VR as an integral part of engineering practice.

This study describes the results of research work on the long-term analysis of land cover changes caused by mining activities in the Strzelin quarries between 1884 and 2023. The primary aim of this study was to analyse long-term landscape changes resulting from granite and gneiss extraction, using a land cover classification adapted to mining conditions. To achieve this, a methodological framework was developed that combines historical cartographic sources with geospatial data, enabling a reconstruction of post-mining land transformations. The framework incorporated rarely utilized historical maps such as 19th-century Messtischblatt maps, with spatial datasets including orthophotos and geospatial databases. The methodology is based on georeferencing and manual vectorisation of open-access data, followed by classification and topological validation to ensure spatial consistency across the time series. The results of the study indicate significant changes in the landscape, in particular an almost threefold increase in the area of mining sites between 2004 and 2023, as well as the appearance of spontaneous vegetation succession and formation of water bodies in areas where mines have been liquidated. The study also documents parallel urbanisation trends and infrastructure development, highlighting the complex interaction between industrial activity and socio-environmental processes. This work contributes to research on land use and land cover (LULC) by extending the time frame of the analysis beyond the limitations of satellite era data and filling a gap in the literature on land use changes caused by mining activities. The proposed approach is transferable to small and medium-sized areas and supports evidence-based spatial planning, land reclamation, and heritage preservation in post-industrial environments on the basis of actions taken in Strzelin and Mikoszów.

VR technologies are playing an increasingly important role in the visualisation of hard-to-reach places, such as underground environments, which is important for the documentation and protection of cultural heritage. The digitisation of such objects allows the creation of a faithful digital twin and its dissemination in the form of immersive experiences. In this study, a comprehensive workflow for the creation of 3D virtual models was developed and illustrated using the part of Podgórze uranium mine as an example. The process included data acquisition, point cloud processing, 3D modeling, optimisation, and integration and integration into a game engine for VR applications. The results show that the obtained models achieved high accuracy, the cloud-to-mesh (C2M) mean errors within ± 14 mm and standard deviations up to 58 mm relative to the input data. Despite the lack of original textures, realistic approximations have been used to enhance authenticity. Interactive elements further enhance the user experience. The results support the preservation of historical sites and its popularisation in educational and tourist applications. The proposed workflow is highly adaptable, making it applicable to other historical and industrial sites.

Ongoing transformations in the European raw materials sector have accelerated the decline of coal mining and the closure of mines across Europe. This process gives rise to post-mining areas, the environmental impact of which does not end with the end of exploitation. In this context, the ability to predict environmental risks at an early stage, based on analyses carried out on similar sites is crucial. Among the various post-mining features, thermally active coal waste dumps represent a persistent environmental legacy of historical and contemporary coal mining. At these sites, spontaneous combustion and self-heating processes can remain active decades after mine closure as a result of exothermic reactions in coal residues and organic matter. These processes generate long-term thermal anomalies, gas emissions, and progressive degradation of soils and ecosystems. Monitoring such sites is therefore essential for understanding associated risks and tracking long-term changes in thermally active areas, with direct relevance for post-mining land use and reclamation process.This study presents an Earth Observation (EO)-based approach for acquiring and analysing Land Surface Temperature (LST) to monitor thermally active coal waste dumps and evaluate their relationship with surface and vegetation conditions. The methodology is based on multi-temporal open-access satellite imagery, enabling the detection of both persistent and seasonal thermal anomalies at local scales while supporting long-term environmental analysis at the regional level. The analysis uses Landsat 5, 8, 9 imagery acquired between 1999 and 2025 and focuses on a thermally active coal waste heap near Nowa Ruda in the Lower Silesian Coal Basin (SW Poland), a region transformed by decades of underground coal mining.Thermal anomalies were mapped and analysed across multiple time steps to assess their spatial patterns and temporal variability. The Self-Heating Intensity Index (SHII) was calculated to quantify the intensity and persistence of thermal activity within post-mining waste materials. LST data were analysed in conjunction with vegetation and surface condition indicators derived from satellite imagery, including NDVI, SAVI, NDMI, NBR and BSI. To understand how thermal patterns and surface condition indicators interact under different moisture and geomorphological conditions at waste dumps, a combination of spatial correlation analyses and seasonal comparisons were used.The results demonstrate spatial associations between elevated LST values and surface characteristics indicative of limited vegetation cover and exposed substrates, whereas areas with lower thermal signatures correspond to more developed surface cover. Temporal analysis reveals differences in the seasonal behaviour of thermal and spectral indicators, allowing for the differentiation of zones with contrasting thermal and surface conditions.To address the persistent environmental impacts of coal mining in the context of ongoing transformations in the energy and raw materials sector, this study applies thermal and spectral data obtained from satellites to monitor thermally active mine waste sites. The results can serve as a reference point for risk assessment in other areas undergoing mine closure, as well as providing insight into potentially dangerous phenomena based on experience from areas with a longer history of post-mining transformation.